Future state prediction errors guide active avoidance behavior by adult zebrafish
Future state prediction errors guide active avoidance behavior by adult zebrafish
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DOI：
10.1101/546440
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发表时间：
2019-02
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影响因子：
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通讯作者：
Makio Torigoe;T. Islam;Hisaya Kakinuma;C. Fung;Takuya Isomura;Hideaki Shimazaki;Tazu Aoki;T. Fukai;H. Okamoto
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文献类型：
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作者：
Makio Torigoe;T. Islam;Hisaya Kakinuma;C. Fung;Takuya Isomura;Hideaki Shimazaki;Tazu Aoki;T. Fukai;H. Okamoto
人类预测未来。为了探究鱼是否也具有这种能力，我们建立了虚拟现实训练系统，对主动回避的成年斑马鱼的端脑神经元进行实时成像，结果发现，在试验开始时，学习过的鱼将两种未来条件视为其通往安全目标的有利状态，即一种具有向后移动的景观，另一种具有安全目标的颜色。两个不同的神经网络监控这些预测与感知的真实外部状态之间的差异。一旦鱼到达目标，另一个团队就会开始工作，以监测鱼是否一直停留在安全目标中。人为增强这些预测错误的操作提高了这些群体的活动，并诱导鱼类做出纠正错误的行为，这表明鱼类设定了行为策略来主动实现这些预测。
Human predicts future. To ask if fish also has this capacity, we established the virtual reality training system with live imaging of the telencephalic neurons of adult zebrafish in the active avoidance and found that, at the onset of the trial, learned fish conceives two future conditions as the favorable status on its way to the safe goal, i.e. one with the backwardly moving landscape and the other with the color of the safe goal. And the two different neural ensembles monitor the discrepancy between these predictions and the perceived real external status. Once fish reaches the goal, another ensemble is set to work to monitor whether fish keeps staying in the safe goal. The manipulation to artificially enhance these prediction errors elevated the activities of these ensembles and induced fish to behave to correct errors, revealing that fish sets behavioral strategy to actively realize these predictions.